abhishekdas.com

Evaluation du site abhishekdas.com

Abhishek Das

 Généré le 10 Avril 2026 08:56

Vieilles statistiques? UPDATE !

Le score est de 66/100

Optimisation du contenu

Titre

Abhishek Das

Longueur : 12

Parfait, votre titre contient entre 10 et 70 caractères.

Description

Research Scientist at Facebook AI Research. Learning to build machines that can see, think, talk and act.

Longueur : 105

Génial, votre balise META description contient entre 70 et 160 caractères.

Mots-clefs

yoda, abhshkdz, abhishek das, sdslabs, jekyll, hacker, developer, pianist, iit roorkee, abdasuee, deep learning, computer vision, neural networks, georgia tech, virginia tech, machine learning

Bien, votre page contient une balise META keywords.

Propriétés Open Graph

Bien, cette page profite des balises META Open Graph.

Propriété Contenu
url http://abhishekdas.com/
site_name Abhishek Das
image http://abhishekdas.com/img/avatar.jpg
image:url http://abhishekdas.com/img/avatar.jpg

Niveaux de titre

H1 H2 H3 H4 H5 H6
7 46 0 0 0 0
  • [H1] Abhishek Das
  • [H1]
  • [H1] News
  • [H1] Bio
  • [H1] Publications
  • [H1] Talks
  • [H1] Side projects
  • [H2] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
  • [H2] The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture
  • [H2] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
  • [H2] AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning
  • [H2] PIRLNav: Pretraining with Imitation and RL Finetuning for ObjectNav
  • [H2] The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis
  • [H2] GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets
  • [H2] Spherical Channels for Modeling Atomic Interactions
  • [H2] Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery
  • [H2] Transfer learning using attentions across atomic systems with graph neural networks (TAAG)
  • [H2] Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale
  • [H2] Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
  • [H2] Rotation Invariant Graph Neural Networks using Spin Convolutions
  • [H2] Automated Video Description for Blind and Low Vision Users
  • [H2] Auxiliary Tasks and Exploration Enable ObjectNav
  • [H2] ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations
  • [H2] The Open Catalyst 2020 (OC20) Dataset and Community Challenges
  • [H2] An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage
  • [H2] Auxiliary Tasks Speed Up Learning PointGoal Navigation
  • [H2] Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline
  • [H2] Building agents that can see, talk, and act
  • [H2] Probing Emergent Semantics in Predictive Agents via Question Answering
  • [H2] Feel The Music: Automatically Generating A Dance For An Input Song
  • [H2] IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL
  • [H2] Improving Generative Visual Dialog by Answering Diverse Questions
  • [H2] TarMAC: Targeted Multi-Agent Communication
  • [H2] Embodied Question Answering in Photorealistic Environments with Point Clouds
  • [H2] Audio-Visual Scene-Aware Dialog
  • [H2] End-to-end Audio Visual Scene-Aware Dialog Using Multimodal Attention-based Video Features
  • [H2] Neural Modular Control for Embodied Question Answering
  • [H2] Embodied Question Answering
  • [H2] Evaluating Visual Conversational Agents via Cooperative Human-AI Games
  • [H2] Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning
  • [H2] Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
  • [H2] Visual Dialog
  • [H2] Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?
  • [H2] aipaygrad.es
  • [H2] aideadlin.es
  • [H2] neural-vqa-attention
  • [H2] neural-vqa
  • [H2] Erdős
  • [H2] graf
  • [H2] HackFlowy
  • [H2] AirMaps
  • [H2] HackView
  • [H2] 8tracks-downloader

Images

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Ratio texte/HTML

Ratio : 25%

Idéal! le ratio de cette page texte/HTML est entre 25 et 70 pour cent.

Flash

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Iframe

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Réécriture d'URLs

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Liens dans la page

Nous avons trouvé un total de 187 lien(s) dont 45 lien(s) vers des fichiers

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Mots-clefs

Nuage de mots-clefs

video batra abhishek visual code zitnick paper das lawrence learning

Cohérence des mots-clefs

Mot-clef Contenu Titre Mots-clefs Description Niveaux de titre
das 26
abhishek 26
paper 24
code 18
video 13

Ergonomie

Url

Domaine : abhishekdas.com

Longueur : 15

Favicon

Génial, votre site web dispose d'un favicon.

Imprimabilité

Aucun style CSS pour optimiser l'impression n'a pu être trouvé.

Langue

Bien. Votre langue est : en.

Dublin Core

Cette page ne profite pas des métadonnées Dublin Core.

Document

Doctype

HTML 5

Encodage

Parfait. Votre charset est UTF-8.

Validité W3C

Erreurs : 0

Avertissements : 0

E-mail confidentialité

Génial, aucune adresse e-mail n'a été trouvé sous forme de texte!

HTML obsolètes

Génial! Nous n'avons pas trouvé de balises HTML obsolètes dans votre code.

Astuces vitesse

Excellent, votre site n'utilise pas de tableaux imbriqués.
Mauvais, votre site web utilise des styles css inline.
Génial, votre site web contient peu de fichiers CSS.
Parfait, votre site web contient peu de fichiers javascript.
Parfait : votre site tire parti de gzip.

Mobile

Optimisation mobile

Icône Apple
Méta tags viewport
Contenu FLASH

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Robots.txt

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